Variational quantum Monte Carlo (VMC) combined with neural-network quantum states offers a novel angle of attack on the curse-of-dimensionality encountered in a particular class of partial differential equations (PDEs); namely, the real- and imaginary time-dependent Schr\"odinger equation. In this paper, we present a simple generalization of VMC applicable to arbitrary time-dependent PDEs, showcasing the technique in the multi-asset Black-Scholes PDE for pricing European options contingent on many correlated underlying assets
International audienceWe propose a neural-network variational quantum algorithm to simulate the time...
In this article, we consider a set of trial wave-functions denoted by $| Q \right>$ and an associate...
The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Qu...
The variational quantum Monte Carlo (VQMC) method has received significant attention because of its ...
The variational quantum Monte Carlo (VQMC) method has received significant attention because of its ...
We propose an algorithm based on variational quantum imaginary time evolution for solving the Feynma...
Inspired by recent progress in quantum algorithms for ordinary and partial differential equations, w...
This is the final version. Available from Wiley via the DOI in this record. Data Availability Statem...
This is the final version. Available from Wiley via the DOI in this record. Data Availability Statem...
A variational quantum algorithm for numerically solving partial differential equations (PDEs) on a q...
The accurate numerical solution of partial differential equations is a central task in numerical ana...
We analyze the accuracy and sample complexity of variational Monte Carlo approaches to simulate the ...
Quantum computers are not yet up to the task of providing computational advantages for practical sto...
Variational quantum algorithms (VQAs) utilize a hybrid quantum-classical architecture to recast prob...
A derivative is a financial security whose value is a function of underlying traded assets and marke...
International audienceWe propose a neural-network variational quantum algorithm to simulate the time...
In this article, we consider a set of trial wave-functions denoted by $| Q \right>$ and an associate...
The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Qu...
The variational quantum Monte Carlo (VQMC) method has received significant attention because of its ...
The variational quantum Monte Carlo (VQMC) method has received significant attention because of its ...
We propose an algorithm based on variational quantum imaginary time evolution for solving the Feynma...
Inspired by recent progress in quantum algorithms for ordinary and partial differential equations, w...
This is the final version. Available from Wiley via the DOI in this record. Data Availability Statem...
This is the final version. Available from Wiley via the DOI in this record. Data Availability Statem...
A variational quantum algorithm for numerically solving partial differential equations (PDEs) on a q...
The accurate numerical solution of partial differential equations is a central task in numerical ana...
We analyze the accuracy and sample complexity of variational Monte Carlo approaches to simulate the ...
Quantum computers are not yet up to the task of providing computational advantages for practical sto...
Variational quantum algorithms (VQAs) utilize a hybrid quantum-classical architecture to recast prob...
A derivative is a financial security whose value is a function of underlying traded assets and marke...
International audienceWe propose a neural-network variational quantum algorithm to simulate the time...
In this article, we consider a set of trial wave-functions denoted by $| Q \right>$ and an associate...
The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Qu...